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Found 5 papers, 1 papers with code
Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models
Further, we emphasize the existence of Quality-Diversity trade-offs in training data and the downstream effects on model performance.
Quality-Diversity through AI Feedback
In many text-generation problems, users may prefer not only a single response, but a diverse range of high-quality outputs from which to choose.
MultiFusion: Fusing Pre-Trained Models for Multi-Lingual, Multi-Modal Image Generation
The recent popularity of text-to-image diffusion models (DM) can largely be attributed to the intuitive interface they provide to users.
M-VADER: A Model for Diffusion with Multimodal Context
We introduce M-VADER: a diffusion model (DM) for image generation where the output can be specified using arbitrary combinations of images and text.
Frequency Gating: Improved Convolutional Neural Networks for Speech Enhancement in the Time-Frequency Domain
One of the strengths of traditional convolutional neural networks (CNNs) is their inherent translational invariance.
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